Python3 for loop over a dict

[ogautier]

Hello!
I am trying to get all the values individually for each asset for example:

BCHUSD
a = 301.340000
b = 301.160000
c = 301.280000

TRXUSD
a = 0.0609450
b = 0.0609440
c = 0.0609540 and so on...

Could someone tell me how I can do it please?

Regards!

import requests import json while True: req = requests.get('https://api.kraken.com/0/public/Ticker?pair=BCHUSD,TRXUSD,XRPUSD')	print(req)	<Response [200]> print(type(req))	<class 'requests.models.Response'> obj = req.json()	print(type(obj))	<class 'dict'> print(obj) {'error': [], 'result': {'BCHUSD': {'a': ['301.340000', '8', '8.000'], 'b': ['301.160000', '5', '5.000'], 'c': ['301.280000', '2.17601336'], 'v': ['24.29958509', '5601.96455701'], 'p': ['301.518130', '277.596849'], 't': [15, 2308], 'l': ['299.000000', '260.000000'], 'h': ['302.390000', '309.900000'], 'o': '299.000000'}, 'TRXUSD': {'a': ['0.0609450', '70500', '70500.000'], 'b': ['0.0609440', '1094', '1094.000'], 'c': ['0.0609540', '360.09238846'], 'v': ['19826.64747345', '9636655.93947494'], 'p': ['0.0610639', '0.0589701'], 't': [22, 1735], 'l': ['0.0608850', '0.0562060'], 'h': ['0.0612840', '0.0618410'], 'o': '0.0611130'}, 'XXRPZUSD': {'a': ['0.69453000', '720', '720.000'], 'b': ['0.69419000', '694', '694.000'], 'c': ['0.69180000', '2196.58617800'], 'v': ['235770.55961560', '28023892.06456976'], 'p': ['0.69880570', '0.66007675'], 't': [415, 10359], 'l': ['0.69121000', '0.62229000'], 'h': ['0.70386000', '0.72105000'], 'o': '0.69935000'}}} for k, v in obj.items(): if type(v) is dict and k: for nk, nv in v.items(): print(nk, nv) BCHUSD {'a': ['298.240000', '11', '11.000'], 'b': ['298.040000', '3', '3.000'], 'c': ['299.000000', '0.89507885'], 'v': ['38.42175237', '5614.56089299'], 'p': ['300.890848', '277.650439'], 't': [24, 2314], 'l': ['299.000000', '260.000000'], 'h': ['302.390000', '309.900000'], 'o': '299.000000'} TRXUSD {'a': ['0.0608250', '4881', '4881.000'], 'b': ['0.0607820', '40500', '40500.000'], 'c': ['0.0608630', '81.94337742'], 'v': ['21067.61432979', '9622286.56922629'], 'p': ['0.0610566', '0.0589675'], 't': [25, 1729], 'l': ['0.0608630', '0.0562060'], 'h': ['0.0612840', '0.0618410'], 'o': '0.0611130'} XXRPZUSD {'a': ['0.69018000', '666', '666.000'], 'b': ['0.69000000', '42829', '42829.000'], 'c': ['0.69022000', '358.00000000'], 'v': ['287549.02071579', '27810492.67564827'], 'p': ['0.69737332', '0.65981291'], 't': [429, 10340], 'l': ['0.69000000', '0.62229000'], 'h': ['0.70386000', '0.72105000'], 'o': '0.69935000'}

[ndc85430]

OK, so nv there is a dict isn't it? You know how to iterate over a dict.

[deanhystad]

You haven't asked a question here. What are you trying to do with req? I would think that if req["error"] is empty that req["result"] will be full of the information you need. What do you want to do with that information?

for currency_tag, currency_info in req["result"].items(): print(currency_tag) for key, value in currency_info.items(): print(key, value)

I would put this in a dataframe.

req = { 'error': [], 'result': { 'BCHUSD': { 'a': ['301.340000', '8', '8.000'], 'b': ['301.160000', '5', '5.000'], 'c': ['301.280000', '2.17601336'], 'v': ['24.29958509', '5601.96455701'], 'p': ['301.518130', '277.596849'], 't': [15, 2308], 'l': ['299.000000', '260.000000'], 'h': ['302.390000', '309.900000'], 'o': '299.000000' }, 'TRXUSD': { 'a': ['0.0609450', '70500', '70500.000'], 'b': ['0.0609440', '1094', '1094.000'], 'c': ['0.0609540', '360.09238846'], 'v': ['19826.64747345', '9636655.93947494'], 'p': ['0.0610639', '0.0589701'], 't': [22, 1735], 'l': ['0.0608850', '0.0562060'], 'h': ['0.0612840', '0.0618410'], 'o': '0.0611130' }, 'XXRPZUSD': { 'a': ['0.69453000', '720', '720.000'], 'b': ['0.69419000', '694', '694.000'], 'c': ['0.69180000', '2196.58617800'], 'v': ['235770.55961560', '28023892.06456976'], 'p': ['0.69880570', '0.66007675'], 't': [415, 10359], 'l': ['0.69121000', '0.62229000'], 'h': ['0.70386000', '0.72105000'], 'o': '0.69935000' } } } import pandas as pd df = pd.DataFrame(req["result"]) print(df)

Output:
 BCHUSD TRXUSD XXRPZUSD a [301.340000, 8, 8.000] [0.0609450, 70500, 70500.000] [0.69453000, 720, 720.000] b [301.160000, 5, 5.000] [0.0609440, 1094, 1094.000] [0.69419000, 694, 694.000] c [301.280000, 2.17601336] [0.0609540, 360.09238846] [0.69180000, 2196.58617800] v [24.29958509, 5601.96455701] [19826.64747345, 9636655.93947494] [235770.55961560, 28023892.06456976] p [301.518130, 277.596849] [0.0610639, 0.0589701] [0.69880570, 0.66007675] t [15, 2308] [22, 1735] [415, 10359] l [299.000000, 260.000000] [0.0608850, 0.0562060] [0.69121000, 0.62229000] h [302.390000, 309.900000] [0.0612840, 0.0618410] [0.70386000, 0.72105000] o 299.000000 0.0611130 0.69935000

You can do lots of interesting things with a dataframe.

[Larz60+]

Or as a function:

dict1 = {'error': [], 'result': {'BCHUSD': {'a': ['301.340000', '8', '8.000'], 'b': ['301.160000', '5', '5.000'], 'c': ['301.280000', '2.17601336'], 'v': ['24.29958509', '5601.96455701'], 'p': ['301.518130', '277.596849'], 't': [15, 2308], 'l': ['299.000000', '260.000000'], 'h': ['302.390000', '309.900000'], 'o': '299.000000'}, 'TRXUSD': {'a': ['0.0609450', '70500', '70500.000'], 'b': ['0.0609440', '1094', '1094.000'], 'c': ['0.0609540', '360.09238846'], 'v': ['19826.64747345', '9636655.93947494'], 'p': ['0.0610639', '0.0589701'], 't': [22, 1735], 'l': ['0.0608850', '0.0562060'], 'h': ['0.0612840', '0.0618410'], 'o': '0.0611130'}, 'XXRPZUSD': {'a': ['0.69453000', '720', '720.000'], 'b': ['0.69419000', '694', '694.000'], 'c': ['0.69180000', '2196.58617800'], 'v': ['235770.55961560', '28023892.06456976'], 'p': ['0.69880570', '0.66007675'], 't': [415, 10359], 'l': ['0.69121000', '0.62229000'], 'h': ['0.70386000', '0.72105000'], 'o': '0.69935000'}}} def display_dict(dictname, level=0): indent = " " * (4 * level) for key, value in dictname.items(): if isinstance(value, dict): print(f'\n{indent}{key}') level += 1 display_dict(value, level) else: print(f'{indent}{key}: {value}') if level > 0: level -= 1 display_dict(dict1)

Output:
error: [] result BCHUSD a: ['301.340000', '8', '8.000'] b: ['301.160000', '5', '5.000'] c: ['301.280000', '2.17601336'] v: ['24.29958509', '5601.96455701'] p: ['301.518130', '277.596849'] t: [15, 2308] l: ['299.000000', '260.000000'] h: ['302.390000', '309.900000'] o: 299.000000 TRXUSD a: ['0.0609450', '70500', '70500.000'] b: ['0.0609440', '1094', '1094.000'] c: ['0.0609540', '360.09238846'] v: ['19826.64747345', '9636655.93947494'] p: ['0.0610639', '0.0589701'] t: [22, 1735] l: ['0.0608850', '0.0562060'] h: ['0.0612840', '0.0618410'] o: 0.0611130 XXRPZUSD a: ['0.69453000', '720', '720.000'] b: ['0.69419000', '694', '694.000'] c: ['0.69180000', '2196.58617800'] v: ['235770.55961560', '28023892.06456976'] p: ['0.69880570', '0.66007675'] t: [415, 10359] l: ['0.69121000', '0.62229000'] h: ['0.70386000', '0.72105000'] o: 0.69935000